Conventional database systems store data in the form of records or rows. Each row includes one or more related items of information. For example, a row can include the date, number, amount and customer for an order. Certain groups of rows are organized into tables. For example, an Orders table can include all of the rows describing the characteristics of orders that have been received.
Users of database systems manipulate and extract information from the tables and rows that make up the system. Such requests are conventionally referred to as queries. Queries can range in complexity from a request for the display of the information in a particular row to an accumulation of data regarding rows and tables that comprise terabytes of information. Users of database systems also insert, delete, and update the information stored in the tables and rows.
Database systems that employ parallel processing can manipulate and extract information from multiple rows and tables at the same time. Such systems can also execute multiple queries at the same time, if those queries do not create conflicts in the use of system resources. Measuring the parallelism of the execution steps of a query can determine the appropriate limit on the system resources used by those steps. One example of measuring parallelism is determining whether a step uses one of the parallel units, some of the parallel units, or all of the parallel units. Those measurements can be referred to respectively as single, partial, and total parallelism.